Postcranial osteometric data from human and 27 North American faunal species

Although nonhuman remains constitute a significant portion of forensic anthropological casework, the potential use of quantitative methods to assess human origins and classify species from gross bone morphology has not been thoroughly investigated. This study aimed to test the utility of a few basic long bone measurements to distinguish human from nonhuman remains and classify species. More than 50,000 measurements were compiled from humans and 27 nonhuman species (mostly North American). Decision trees developed from the long bone data differentiate human and nonhuman remains with more than 90% accuracy (>98% accuracy for the human sample), even if all long bones are pooled. Stepwise discriminant function results were slightly lower (>87.4% overall accuracy). The quantitative models can be used to support visual identifications or preliminarily assess forensic significance at scenes. For species classification, bone-specific discriminant functions returned accuracies between 77.7% and 89.1%, but classification results varied highly across species. A web tool, OsteoID, was developed from the study data where users can input basic measurements, and photographs of potential bones/species are returned for visual identification. Additional resources (e.g., 3D scans) are provided, creating an important resource for forensic anthropologists and others to assist in skeletal species identification and comparative osteology training.

Methods
Osteometric data (maximum lengths, proximal and distal maximum widths (medio-lateral) and depths (antero-posterio) and mishaft maximum and minimum diameters) were collected from human and nonhuman bones curated in museums and institutions using digital calipers. Additional data were compiled from previously published studies and publicly available skeletal databases. Citations are provided for data collected from these literature/database sources. The data uploaded here contains the raw measurements.